{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\thies\OneDrive\00_Promotion\00_Output\00_Paper\2022_Predicting_Econ_Sanctions\Empirics\20231214_Replication\Log_files/02a_Success_ordered_probit.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}18 Dec 2023, 16:22:05
{txt}
{com}. 
. ***************************************************************
. ***EU***
. ***************************************************************
. 
. *Prepare data
. use"Dataset.dta", clear
{txt}
{com}. keep if sender=="EU"
{txt}(10,154 observations deleted)

{com}. 
. * Setup
. ** Filter for cases of importance
. keep if pot_sanctioned_countries == 1
{txt}(1,296 observations deleted)

{com}. ** Set Panel Structure
. xtset ccodecow year
{res}
{col 1}{txt:Panel variable: }{res:ccodecow}{txt: (unbalanced)}
{p 1 16 2}{txt:Time variable: }{res:year}{txt:, }{res:{bind:1989}}{txt: to }{res:{bind:2015}}{p_end}
{txt}{col 10}Delta: {res}1 unit
{txt}
{com}. 
. * Independent Variables
. gen ln_oil_gas_value_2014 = ln(oil_gas_value_2014+1)
{txt}(197 missing values generated)

{com}. gen sender_colony=0
{txt}
{com}. replace sender_colony=1 if ht_colonial==2 | ht_colonial==3 | ht_colonial==6 | ht_colonial==7 | ht_colonial==8 | ht_colonial==9 | ht_colonial==10
{txt}(2,539 real changes made)

{com}. 
. gen sender_additional=cond(threatUS==1 | impositionUS == 1, 1, 0)
{txt}
{com}. gen only_threat=cond(threatEU==1 & impositionEU == 0, 1, 0)
{txt}
{com}. gen sender_trade = ln_EU_Trade_Eurostat
{txt}(20 missing values generated)

{com}. gen coup_dummy = coup1
{txt}(5 missing values generated)

{com}. replace coup_dummy = 0 if coup_dummy == 1
{txt}(61 real changes made)

{com}. replace coup_dummy = 1 if coup_dummy == 2
{txt}(45 real changes made)

{com}. 
. * Variable indicating sanction onset
. replace caseid=0 if caseid==.
{txt}(3,299 real changes made)

{com}. gen sanctiononset = (caseid-l.caseid)
{txt}(147 missing values generated)

{com}. replace sanctiononset=1 if sanctiononset > 1 & !missing(sanctiononset)
{txt}(89 real changes made)

{com}. replace sanctiononset=0 if sanctiononset < 0
{txt}(68 real changes made)

{com}. replace sanctiononset=. if sanctiononset == 0 & (sanction_dyad == 1 | threat_dyad == 1)
{txt}(384 real changes made, 384 to missing)

{com}. tab sanctiononset

{txt}sanctionons {c |}
         et {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}      3,161       97.26       97.26
{txt}          1 {c |}{res}         89        2.74      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      3,250      100.00
{txt}
{com}. 
. * include threat intensity into intensity measure
. gen intensity = impositionEU_target
{txt}(3,330 missing values generated)

{com}. replace intensity=threatEU_target if missing(intensity)
{txt}(31 real changes made)

{com}. 
. * combine intensity 1-2 & 3-5, because almost no cases
. *3-4,5
. replace intensity=1 if intensity==1 | intensity==2 
{txt}(10 real changes made)

{com}. replace intensity=2 if intensity==3 | intensity==4 
{txt}(386 real changes made)

{com}. replace intensity=3 if intensity==5
{txt}(20 real changes made)

{com}. replace intensity=4 if intensity==6
{txt}(51 real changes made)

{com}. 
. * Gradualism
. gen gradualism = impositionEU_gradualism
{txt}(3,330 missing values generated)

{com}. replace gradualism=1 if missing(impositionEU_gradualism) & sanctiononset==1
{txt}(19 real changes made)

{com}. 
. * Ordinal success variable based on HSE score
. * 6; 12
. gen ordsuccess=0 if sanctiononset == 1
{txt}(3,692 missing values generated)

{com}. replace ordsuccess=1 if HSEscore == 6 | HSEscore == 9
{txt}(203 real changes made)

{com}. replace ordsuccess=2 if HSEscore == 12 | HSEscore == 16
{txt}(63 real changes made)

{com}. 
. * create training and test variable
. gen ordsuccess_train= ordsuccess * sanctiononset if year < 2009
{txt}(3,712 missing values generated)

{com}. gen ordsuccess_test= ordsuccess*sanctiononset if year >= 2009
{txt}(3,761 missing values generated)

{com}. 
. 
. ** Regressions
. eststo:ologit ordsuccess_train i.intensity L.v2x_polyarchy i.L.gd_ptss i.L.coup_dummy i.L.one_sided_violence i.L.conflict i.L.mid_terr_integrity L.ln_GDPpc_imputed L.sender_trade L.ln_oil_gas_value_2014 i.L.sender_colony i.L.defense_alliance i.sender_additional i.only_threat i.gradualism 

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-69.606204}  
Iteration 1:{space 3}log likelihood = {res:-56.950032}  
Iteration 2:{space 3}log likelihood = {res:-56.557872}  
Iteration 3:{space 3}log likelihood = {res:-56.556002}  
Iteration 4:{space 3}log likelihood = {res:-56.556002}  
{res}
{txt}{col 1}Ordered logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:67}
{txt}{col 57}{lalign 13:LR chi2({res:22})}{col 70} = {res}{ralign 6:26.10}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.2474}
{txt}{col 1}{lalign 14:Log likelihood}{col 15} = {res}{ralign 10:-56.556002}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.1875}

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}     ordsuccess_train{col 23}{c |} Coefficient{col 35}  Std. err.{col 47}      z{col 55}   P>|z|{col 63}     [95% con{col 76}f. interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}intensity {c |}
{space 19}2  {c |}{col 23}{res}{space 2} 1.167981{col 35}{space 2} 1.076668{col 46}{space 1}    1.08{col 55}{space 3}0.278{col 63}{space 4}-.9422503{col 76}{space 3} 3.278212
{txt}{space 19}3  {c |}{col 23}{res}{space 2} 2.224042{col 35}{space 2} 2.652869{col 46}{space 1}    0.84{col 55}{space 3}0.402{col 63}{space 4}-2.975484{col 76}{space 3} 7.423569
{txt}{space 19}4  {c |}{col 23}{res}{space 2} 3.641993{col 35}{space 2} 2.337863{col 46}{space 1}    1.56{col 55}{space 3}0.119{col 63}{space 4}-.9401332{col 76}{space 3}  8.22412
{txt}{space 21} {c |}
{space 8}v2x_polyarchy {c |}
{space 18}L1. {c |}{col 23}{res}{space 2} .6678296{col 35}{space 2}  2.07244{col 46}{space 1}    0.32{col 55}{space 3}0.747{col 63}{space 4}-3.394079{col 76}{space 3} 4.729738
{txt}{space 21} {c |}
{space 12}L.gd_ptss {c |}
{space 19}2  {c |}{col 23}{res}{space 2} 1.253311{col 35}{space 2} 1.381881{col 46}{space 1}    0.91{col 55}{space 3}0.364{col 63}{space 4}-1.455127{col 76}{space 3} 3.961749
{txt}{space 19}3  {c |}{col 23}{res}{space 2} .2851296{col 35}{space 2} 1.404021{col 46}{space 1}    0.20{col 55}{space 3}0.839{col 63}{space 4}  -2.4667{col 76}{space 3}  3.03696
{txt}{space 19}4  {c |}{col 23}{res}{space 2} .1853127{col 35}{space 2} 1.600562{col 46}{space 1}    0.12{col 55}{space 3}0.908{col 63}{space 4} -2.95173{col 76}{space 3} 3.322356
{txt}{space 19}5  {c |}{col 23}{res}{space 2}  .006749{col 35}{space 2} 1.652432{col 46}{space 1}    0.00{col 55}{space 3}0.997{col 63}{space 4}-3.231957{col 76}{space 3} 3.245455
{txt}{space 21} {c |}
{space 9}L.coup_dummy {c |}
{space 19}1  {c |}{col 23}{res}{space 2}-2.467435{col 35}{space 2} 1.305895{col 46}{space 1}   -1.89{col 55}{space 3}0.059{col 63}{space 4}-5.026943{col 76}{space 3} .0920732
{txt}{space 21} {c |}
{space 1}L.one_sided_violence {c |}
{space 19}1  {c |}{col 23}{res}{space 2}-.2521301{col 35}{space 2} .7820528{col 46}{space 1}   -0.32{col 55}{space 3}0.747{col 63}{space 4}-1.784925{col 76}{space 3} 1.280665
{txt}{space 21} {c |}
{space 11}L.conflict {c |}
{space 19}1  {c |}{col 23}{res}{space 2} .1950743{col 35}{space 2} .8473237{col 46}{space 1}    0.23{col 55}{space 3}0.818{col 63}{space 4} -1.46565{col 76}{space 3} 1.855798
{txt}{space 21} {c |}
{space 1}L.mid_terr_integrity {c |}
{space 19}1  {c |}{col 23}{res}{space 2}-.3111678{col 35}{space 2} 1.073519{col 46}{space 1}   -0.29{col 55}{space 3}0.772{col 63}{space 4}-2.415226{col 76}{space 3}  1.79289
{txt}{space 21} {c |}
{space 5}ln_GDPpc_imputed {c |}
{space 18}L1. {c |}{col 23}{res}{space 2} .4089216{col 35}{space 2} .4103786{col 46}{space 1}    1.00{col 55}{space 3}0.319{col 63}{space 4}-.3954057{col 76}{space 3} 1.213249
{txt}{space 21} {c |}
{space 9}sender_trade {c |}
{space 18}L1. {c |}{col 23}{res}{space 2}-.1604168{col 35}{space 2} .2750777{col 46}{space 1}   -0.58{col 55}{space 3}0.560{col 63}{space 4}-.6995591{col 76}{space 3} .3787255
{txt}{space 21} {c |}
ln_oil_gas_value_2014 {c |}
{space 18}L1. {c |}{col 23}{res}{space 2} -.033819{col 35}{space 2} .0452019{col 46}{space 1}   -0.75{col 55}{space 3}0.454{col 63}{space 4}-.1224132{col 76}{space 3} .0547751
{txt}{space 21} {c |}
{space 6}L.sender_colony {c |}
{space 19}1  {c |}{col 23}{res}{space 2} .5149969{col 35}{space 2} .7111776{col 46}{space 1}    0.72{col 55}{space 3}0.469{col 63}{space 4}-.8788856{col 76}{space 3} 1.908879
{txt}{space 21} {c |}
{space 3}L.defense_alliance {c |}
{space 19}1  {c |}{col 23}{res}{space 2} .6941814{col 35}{space 2} .9772535{col 46}{space 1}    0.71{col 55}{space 3}0.477{col 63}{space 4}  -1.2212{col 76}{space 3} 2.609563
{txt}{space 21} {c |}
{space 2}1.sender_additional {c |}{col 23}{res}{space 2} 1.559661{col 35}{space 2} .7144559{col 46}{space 1}    2.18{col 55}{space 3}0.029{col 63}{space 4} .1593529{col 76}{space 3} 2.959968
{txt}{space 8}1.only_threat {c |}{col 23}{res}{space 2}-.6411788{col 35}{space 2} .7139676{col 46}{space 1}   -0.90{col 55}{space 3}0.369{col 63}{space 4} -2.04053{col 76}{space 3}  .758172
{txt}{space 21} {c |}
{space 11}gradualism {c |}
{space 19}2  {c |}{col 23}{res}{space 2}-.8438355{col 35}{space 2} 1.627801{col 46}{space 1}   -0.52{col 55}{space 3}0.604{col 63}{space 4}-4.034267{col 76}{space 3} 2.346596
{txt}{space 19}3  {c |}{col 23}{res}{space 2} .1944576{col 35}{space 2} 1.419642{col 46}{space 1}    0.14{col 55}{space 3}0.891{col 63}{space 4} -2.58799{col 76}{space 3} 2.976906
{txt}{space 19}4  {c |}{col 23}{res}{space 2}-1.751121{col 35}{space 2} 1.236174{col 46}{space 1}   -1.42{col 55}{space 3}0.157{col 63}{space 4}-4.173978{col 76}{space 3} .6717364
{txt}{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}/cut1 {c |}{col 23}{res}{space 2} 1.367256{col 35}{space 2} 4.988639{col 63}{space 4}-8.410297{col 76}{space 3} 11.14481
{txt}{space 16}/cut2 {c |}{col 23}{res}{space 2} 3.876467{col 35}{space 2} 5.003059{col 63}{space 4}-5.929349{col 76}{space 3} 13.68228
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
({res}est1{txt} stored)

{com}. 
. *Predictions
. predict sucEU*, pr
{txt}(3333 missing values generated)

{com}. gen sucEU=1*sucEU2 + 2*sucEU3
{txt}(3,333 missing values generated)

{com}. *drop sucEU sucEU1 sucEU2 sucEU3
. gen bin_sucEU = cond(sucEU >=1.33, 2, cond(sucEU >=.66, 1, 0))
{txt}
{com}. replace bin_sucEU=. if missing(sucEU)
{txt}(3,333 real changes made, 3,333 to missing)

{com}. tab ordsuccess_test bin_sucEU

{txt}ordsuccess {c |}            bin_sucEU
     _test {c |}         0          1          2 {c |}     Total
{hline 11}{c +}{hline 33}{c +}{hline 10}
         0 {c |}{res}         6          4          0 {txt}{c |}{res}        10 
{txt}         1 {c |}{res}         2          3          2 {txt}{c |}{res}         7 
{txt}         2 {c |}{res}         1          0          1 {txt}{c |}{res}         2 
{txt}{hline 11}{c +}{hline 33}{c +}{hline 10}
     Total {c |}{res}         9          7          3 {txt}{c |}{res}        19 
{txt}
{com}. tab2xl ordsuccess_test bin_sucEU using Main_Article\EU_Success_Confusion_Matrix, col(1) row(1)
{res}{txt}file {bf:Main_Article\EU_Success_Confusion_Matrix.xlsx} saved

{com}. 
. * Model evaluation
. * Cohen's Kappa (weighted) .28
. kap ordsuccess_test bin_sucEU, wgt(w) 

{txt}Ratings weighted by:
{res}   1.0000   0.5000   0.0000
   0.5000   1.0000   0.5000
   0.0000   0.5000   1.0000

{txt}{col 14}Expected
Agreement   agreement     Kappa   Std. err.         Z      Prob>Z
{hline 65}
{res}  73.68%      63.43%     0.2803     0.1807       1.55      0.0604
{txt}
{com}. 
. * predict for different intensities
. * intensity = 1
. replace intensity=1 if intensity !=.
{txt}(457 real changes made)

{com}. 
. predict sucEUlow*, pr
{txt}(3333 missing values generated)

{com}. 
. gen sucEUlow=1*sucEUlow2 + 2*sucEUlow3 
{txt}(3,333 missing values generated)

{com}. 
. * intensity = 2
. replace intensity=2 if intensity !=.
{txt}(482 real changes made)

{com}. predict sucEUmed*, pr
{txt}(3333 missing values generated)

{com}. 
. gen sucEUmed=1*sucEUmed2 + 2*sucEUmed3 
{txt}(3,333 missing values generated)

{com}. 
. * intensity = 3
. replace intensity=3 if intensity !=.
{txt}(482 real changes made)

{com}. 
. predict sucEUhigh*, pr
{txt}(3333 missing values generated)

{com}. gen sucEUhigh = 1*sucEUhigh2 + 2*sucEUhigh3 
{txt}(3,333 missing values generated)

{com}. 
. * intensity = 4
. replace intensity=4 if intensity !=.
{txt}(482 real changes made)

{com}. 
. predict sucEUhigher*, pr
{txt}(3333 missing values generated)

{com}. gen sucEUhigher = 1*sucEUhigher2 + 2*sucEUhigher3 
{txt}(3,333 missing values generated)

{com}. 
. drop if missing(ordsuccess_test)
{txt}(3,761 observations deleted)

{com}. 
. * Save dataset outcomes to excel. 
. export excel sender year cname caseid HSEscore ordsuccess_test sucEU* using "Supplemental_Material\EU_Case_level_Success_Results", firstrow(variables) replace
{res}{txt}file {bf:Supplemental_Material\EU_Case_level_Success_Results.xls} saved

{com}. 
. 
. ***************************************************************
. ***US***
. ***************************************************************
. 
. *Prepare data
. use"Dataset.dta", clear
{txt}
{com}. keep if sender=="US"
{txt}(10,154 observations deleted)

{com}. 
. * Setup
. ** Filter for cases of importance
. keep if pot_sanctioned_countries == 1
{txt}(1,296 observations deleted)

{com}. ** Panel structure
. xtset ccodecow year
{res}
{col 1}{txt:Panel variable: }{res:ccodecow}{txt: (unbalanced)}
{p 1 16 2}{txt:Time variable: }{res:year}{txt:, }{res:{bind:1989}}{txt: to }{res:{bind:2015}}{p_end}
{txt}{col 10}Delta: {res}1 unit
{txt}
{com}. 
. * Independent variables
. gen ln_oil_gas_value_2014 = ln(oil_gas_value_2014+1)
{txt}(197 missing values generated)

{com}. gen sender_colony = US_colony
{txt}(13 missing values generated)

{com}. gen coup_dummy = coup1
{txt}(5 missing values generated)

{com}. replace coup_dummy=0 if coup1==1
{txt}(61 real changes made)

{com}. replace coup_dummy=1 if coup1==2
{txt}(45 real changes made)

{com}. 
. gen sender_additional=cond(threatEU==1 | impositionEU == 1, 1, 0)
{txt}
{com}. gen only_threat=cond(threatUS==1 & impositionUS == 0, 1, 0)
{txt}
{com}. gen sender_trade = ln_US_Trade_COW
{txt}(234 missing values generated)

{com}. 
. * Variable for sanction onset
. replace caseid=0 if caseid==.
{txt}(2,793 real changes made)

{com}. gen sanctiononset = (caseid-l.caseid)
{txt}(147 missing values generated)

{com}. replace sanctiononset=1 if sanctiononset > 1 & !missing(sanctiononset)
{txt}(178 real changes made)

{com}. replace sanctiononset=0 if sanctiononset < 0
{txt}(123 real changes made)

{com}. replace sanctiononset=. if sanctiononset == 0 & (sanction_dyad == 1 | threat_dyad == 1)
{txt}(791 real changes made, 791 to missing)

{com}. tab sanctiononset

{txt}sanctionons {c |}
         et {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}      2,665       93.74       93.74
{txt}          1 {c |}{res}        178        6.26      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      2,843      100.00
{txt}
{com}. 
. * include threat intensity into intensity measure
. gen intensity = impositionUS_target
{txt}(2,920 missing values generated)

{com}. replace intensity=threatUS_target if missing(intensity)
{txt}(127 real changes made)

{com}. 
. * combine intensity 1-2 & 3-5, because almost no cases
. *3-4,5
. replace intensity=1 if intensity==1 | intensity==2 
{txt}(63 real changes made)

{com}. replace intensity=2 if intensity==3 | intensity==4 
{txt}(683 real changes made)

{com}. replace intensity=3 if intensity==5
{txt}(63 real changes made)

{com}. replace intensity=4 if intensity==6
{txt}(159 real changes made)

{com}. 
. * Gradualism
. gen gradualism = impositionUS_gradualism
{txt}(2,924 missing values generated)

{com}. replace gradualism=1 if missing(impositionUS_gradualism) & sanctiononset==1
{txt}(57 real changes made)

{com}. 
. * HSE score
. * 6; 12
. gen ordsuccess=0 if sanctiononset == 1
{txt}(3,603 missing values generated)

{com}. replace ordsuccess=1 if HSEscore == 6 | HSEscore == 9
{txt}(339 real changes made)

{com}. replace ordsuccess=2 if HSEscore == 12 | HSEscore == 16
{txt}(132 real changes made)

{com}. 
. * create training and test variable
. gen ordsuccess_train= ordsuccess*sanctiononset if year < 2009
{txt}(3,639 missing values generated)

{com}. gen ordsuccess_test= ordsuccess*sanctiononset if year >= 2009
{txt}(3,745 missing values generated)

{com}. 
. 
. ** Regressions
. eststo:ologit ordsuccess_train i.intensity L.v2x_polyarchy i.L.gd_ptss i.L.one_sided_violence i.L.conflict i.L.mid_terr_integrity L.ln_GDPpc_imputed L.sender_trade L.ln_oil_gas_value_2014 i.L.defense_alliance i.sender_additional i.only_threat i.gradualism 

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-145.45174}  
Iteration 1:{space 3}log likelihood = {res:-126.69559}  
Iteration 2:{space 3}log likelihood = {res:-126.36796}  
Iteration 3:{space 3}log likelihood = {res:-126.36723}  
Iteration 4:{space 3}log likelihood = {res:-126.36723}  
{res}
{txt}{col 1}Ordered logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:134}
{txt}{col 57}{lalign 13:LR chi2({res:20})}{col 70} = {res}{ralign 6:38.17}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.0084}
{txt}{col 1}{lalign 14:Log likelihood}{col 15} = {res}{ralign 10:-126.36723}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.1312}

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}     ordsuccess_train{col 23}{c |} Coefficient{col 35}  Std. err.{col 47}      z{col 55}   P>|z|{col 63}     [95% con{col 76}f. interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}intensity {c |}
{space 19}2  {c |}{col 23}{res}{space 2} .3728731{col 35}{space 2} .5930604{col 46}{space 1}    0.63{col 55}{space 3}0.530{col 63}{space 4} -.789504{col 76}{space 3}  1.53525
{txt}{space 19}3  {c |}{col 23}{res}{space 2} -.501967{col 35}{space 2} 1.491106{col 46}{space 1}   -0.34{col 55}{space 3}0.736{col 63}{space 4} -3.42448{col 76}{space 3} 2.420546
{txt}{space 19}4  {c |}{col 23}{res}{space 2}-2.062238{col 35}{space 2}  1.44101{col 46}{space 1}   -1.43{col 55}{space 3}0.152{col 63}{space 4}-4.886567{col 76}{space 3} .7620903
{txt}{space 21} {c |}
{space 8}v2x_polyarchy {c |}
{space 18}L1. {c |}{col 23}{res}{space 2} .6263083{col 35}{space 2} 1.035348{col 46}{space 1}    0.60{col 55}{space 3}0.545{col 63}{space 4}-1.402937{col 76}{space 3} 2.655553
{txt}{space 21} {c |}
{space 12}L.gd_ptss {c |}
{space 19}2  {c |}{col 23}{res}{space 2} .3543697{col 35}{space 2}  .806841{col 46}{space 1}    0.44{col 55}{space 3}0.661{col 63}{space 4} -1.22701{col 76}{space 3} 1.935749
{txt}{space 19}3  {c |}{col 23}{res}{space 2} .0654858{col 35}{space 2} .8310871{col 46}{space 1}    0.08{col 55}{space 3}0.937{col 63}{space 4}-1.563415{col 76}{space 3} 1.694387
{txt}{space 19}4  {c |}{col 23}{res}{space 2} .2480753{col 35}{space 2} .9726217{col 46}{space 1}    0.26{col 55}{space 3}0.799{col 63}{space 4}-1.658228{col 76}{space 3} 2.154379
{txt}{space 19}5  {c |}{col 23}{res}{space 2}  .861169{col 35}{space 2}   1.0797{col 46}{space 1}    0.80{col 55}{space 3}0.425{col 63}{space 4}-1.255003{col 76}{space 3} 2.977341
{txt}{space 21} {c |}
{space 1}L.one_sided_violence {c |}
{space 19}1  {c |}{col 23}{res}{space 2}-.1177623{col 35}{space 2} .5309427{col 46}{space 1}   -0.22{col 55}{space 3}0.824{col 63}{space 4}-1.158391{col 76}{space 3} .9228663
{txt}{space 21} {c |}
{space 11}L.conflict {c |}
{space 19}1  {c |}{col 23}{res}{space 2}-.4257443{col 35}{space 2} .5469378{col 46}{space 1}   -0.78{col 55}{space 3}0.436{col 63}{space 4}-1.497723{col 76}{space 3} .6462342
{txt}{space 21} {c |}
{space 1}L.mid_terr_integrity {c |}
{space 19}1  {c |}{col 23}{res}{space 2}-.0583877{col 35}{space 2} .7149333{col 46}{space 1}   -0.08{col 55}{space 3}0.935{col 63}{space 4}-1.459631{col 76}{space 3} 1.342856
{txt}{space 21} {c |}
{space 5}ln_GDPpc_imputed {c |}
{space 18}L1. {c |}{col 23}{res}{space 2}-.2574002{col 35}{space 2} .2443153{col 46}{space 1}   -1.05{col 55}{space 3}0.292{col 63}{space 4}-.7362494{col 76}{space 3} .2214489
{txt}{space 21} {c |}
{space 9}sender_trade {c |}
{space 18}L1. {c |}{col 23}{res}{space 2}-.0642116{col 35}{space 2} .1424191{col 46}{space 1}   -0.45{col 55}{space 3}0.652{col 63}{space 4} -.343348{col 76}{space 3} .2149248
{txt}{space 21} {c |}
ln_oil_gas_value_2014 {c |}
{space 18}L1. {c |}{col 23}{res}{space 2}-.0167155{col 35}{space 2} .0245898{col 46}{space 1}   -0.68{col 55}{space 3}0.497{col 63}{space 4}-.0649107{col 76}{space 3} .0314797
{txt}{space 21} {c |}
{space 3}L.defense_alliance {c |}
{space 19}1  {c |}{col 23}{res}{space 2}-.4894509{col 35}{space 2} .4865016{col 46}{space 1}   -1.01{col 55}{space 3}0.314{col 63}{space 4}-1.442977{col 76}{space 3} .4640748
{txt}{space 21} {c |}
{space 2}1.sender_additional {c |}{col 23}{res}{space 2}  .240947{col 35}{space 2}  .450487{col 46}{space 1}    0.53{col 55}{space 3}0.593{col 63}{space 4}-.6419912{col 76}{space 3} 1.123885
{txt}{space 8}1.only_threat {c |}{col 23}{res}{space 2} 1.634658{col 35}{space 2} .4436797{col 46}{space 1}    3.68{col 55}{space 3}0.000{col 63}{space 4} .7650616{col 76}{space 3} 2.504254
{txt}{space 21} {c |}
{space 11}gradualism {c |}
{space 19}2  {c |}{col 23}{res}{space 2}-.2666606{col 35}{space 2} 1.216703{col 46}{space 1}   -0.22{col 55}{space 3}0.827{col 63}{space 4}-2.651355{col 76}{space 3} 2.118034
{txt}{space 19}3  {c |}{col 23}{res}{space 2} -.336517{col 35}{space 2} 1.068282{col 46}{space 1}   -0.32{col 55}{space 3}0.753{col 63}{space 4}-2.430312{col 76}{space 3} 1.757278
{txt}{space 19}4  {c |}{col 23}{res}{space 2}  .434083{col 35}{space 2} .7081005{col 46}{space 1}    0.61{col 55}{space 3}0.540{col 63}{space 4}-.9537684{col 76}{space 3} 1.821934
{txt}{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}/cut1 {c |}{col 23}{res}{space 2}-2.087611{col 35}{space 2} 1.819309{col 63}{space 4}-5.653392{col 76}{space 3}  1.47817
{txt}{space 16}/cut2 {c |}{col 23}{res}{space 2}-.2240531{col 35}{space 2} 1.812247{col 63}{space 4}-3.775991{col 76}{space 3} 3.327885
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
({res}est2{txt} stored)

{com}. 
. *Predictions
. predict sucUS*, pr
{txt}(2920 missing values generated)

{com}. gen sucUS=1*sucUS2 + 2*sucUS3
{txt}(2,920 missing values generated)

{com}. *drop sucUS sucUS1 sucUS2 sucUS3
. gen bin_sucUS = cond(sucUS >=1.33, 2, cond(sucUS >=.66, 1, 0))
{txt}
{com}. replace bin_sucUS=. if missing(sucUS)
{txt}(2,920 real changes made, 2,920 to missing)

{com}. tab2xl ordsuccess_test bin_sucUS using Main_Article\US_Success_Confusion_Matrix, col(1) row(1)
{res}{txt}file {bf:Main_Article\US_Success_Confusion_Matrix.xlsx} saved

{com}. 
. * Model Evaluation
. * Cohen's Kappa (weighted) .24
. kap ordsuccess_test bin_sucUS, wgt(w)

{txt}Ratings weighted by:
{res}   1.0000   0.5000   0.0000
   0.5000   1.0000   0.5000
   0.0000   0.5000   1.0000

{txt}{col 14}Expected
Agreement   agreement     Kappa   Std. err.         Z      Prob>Z
{hline 65}
{res}  72.86%      64.12%     0.2435     0.1186       2.05      0.0200
{txt}
{com}. 
. 
. * predict for different intensities
. * intensity = 1
. replace intensity=1 if intensity !=.
{txt}(905 real changes made)

{com}. 
. predict sucUSlow*, pr
{txt}(2920 missing values generated)

{com}. 
. gen sucUSlow=1*sucUSlow2 + 2*sucUSlow3 
{txt}(2,920 missing values generated)

{com}. 
. * intensity = 2
. replace intensity=2 if intensity !=.
{txt}(988 real changes made)

{com}. predict sucUSmed*, pr
{txt}(2920 missing values generated)

{com}. 
. gen sucUSmed=1*sucUSmed2 + 2*sucUSmed3 
{txt}(2,920 missing values generated)

{com}. 
. * intensity = 3
. replace intensity=3 if intensity !=.
{txt}(988 real changes made)

{com}. 
. predict sucUShigh*, pr
{txt}(2920 missing values generated)

{com}. gen sucUShigh = 1*sucUShigh2 + 2*sucUShigh3 
{txt}(2,920 missing values generated)

{com}. 
. * intensity = 4
. replace intensity=4 if intensity !=.
{txt}(988 real changes made)

{com}. 
. predict sucUShigher*, pr
{txt}(2920 missing values generated)

{com}. gen sucUShigher = 1*sucUShigher2 + 2*sucUShigher3 
{txt}(2,920 missing values generated)

{com}. 
. drop if missing(ordsuccess_test)
{txt}(3,745 observations deleted)

{com}. 
. * Save dataset outcomes to excel. 
. export excel sender year cname caseid HSEscore ordsuccess_test sucUS* using "Supplemental_Material\US_Case_level_Success_Results", firstrow(variables) replace
{res}{txt}file {bf:Supplemental_Material\US_Case_level_Success_Results.xls} saved

{com}. 
. *Output
. esttab est1 est2 using Supplemental_Material\Regression_Tables\Regressions_Success.rtf, se scalars(chi2 p ll r2_p) keep(L.v2x_polyarchy 2L.gd_ptss 3L.gd_ptss 4L.gd_ptss 5L.gd_ptss 1L.coup_dummy 1L.one_sided_violence 1L.conflict 1L.mid_terr_integrity L.ln_GDPpc_imputed L.sender_trade L.ln_oil_gas_value_2014 1L.sender_colony 1L.defense_alliance 1.sender_additional 1.only_threat 2.intensity 3.intensity 4.intensity 2.gradualism 3.gradualism 4.gradualism ) order(L.v2x_polyarchy 2L.gd_ptss 3L.gd_ptss 4L.gd_ptss 5L.gd_ptss 1L.coup_dummy 1L.one_sided_violence 1L.conflict 1L.mid_terr_integrity L.ln_GDPpc_imputed L.sender_trade L.ln_oil_gas_value_2014 1L.defense_alliance 1L.sender_colony 1.only_threat 1.sender_additional 2.intensity 3.intensity 4.intensity 2.gradualism 3.gradualism 4.gradualism) label legend varlabels(L.v2x_polyarchy Dem._Index 2L.gd_ptss Pol._Terror_2 3L.gd_ptss Pol._Terror_3 4L.gd_ptss Pol._Terror_4 5L.gd_ptss Pol._Terror_5 1L.coup_dummy Mil._Coup 1L.one_sided_violence One-sided_Violence 1L.conflict Armed_Conflict 1L.mid_terr_integrity Terr._Integrity L.ln_GDPpc_imputed GDP_p.c. L.sender_trade Sender_Trade L.ln_oil_gas_value_2014 Target_Oil_Gas_Exports 1L.sender_colony Sender_Colony 1L.defense_alliance Defense_Alliance 1.sender_additional Multilateral_US/EU 1.only_threat Threat 2.intensity Intensity_2 3.intensity Intensity_3 4.intensity Intensity_4 2.gradualism Gradualism_2 3.gradualism Gradualism_3 4.gradualism Gradualism_4) mtitles("EU" "US") eqlabel(" ") wide star(* 0.10 ** 0.05 ** 0.01)
{res}{txt}(output written to {browse  `"Supplemental_Material\Regression_Tables\Regressions_Success.rtf"'})

{com}. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\thies\OneDrive\00_Promotion\00_Output\00_Paper\2022_Predicting_Econ_Sanctions\Empirics\20231214_Replication\Log_files/02a_Success_ordered_probit.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}18 Dec 2023, 16:22:08
{txt}{.-}
{smcl}
{txt}{sf}{ul off}